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Diminished estimate techniques for image quality assessment examine the overall quality using only partially retrieved features from the reference image. The main goal of these methods is to make objective evaluation flexible enough to accommodate the influence of any new visual distortion. The research provides a rapid approach for quality assessment of color photographs based on this concept by altering the structural similarity index measure (SSIM) index in a neutrosophic environment. The SSIM family is a set of parameters that have demonstrated a promising approach in the analysis of reference picture tasks. The current study deals with the exploitation of the concept to use Single-Valued Neutrosophic Sets (SVNSs) for evaluating image quality. Neutrosophic divergence was being constructed for an image and its comparison with other SSIM is presented. Resultantly, a correlation was observed between the proposed divergence and SSIM, which gave accurate informatics. Additionally, the results were presented on a real line which reflects clear information on image convergence and divergence. The uncertainty in the allocation of membership is called the hesitation degree, fuzzy sets have gained a lot of traction in numerous domains of signal and image processing. Based on generalized exponential fuzzy entropy, a trustworthy Image Quality Assessment is proposed. [ABSTRACT FROM AUTHOR]